Título Time Series Segmentation and Statistical Characterisation of the Spanish Stock Market Ibex-35 Index
Autores Cruz-Ramirez, M. , de la Paz-Marin, M. , PÉREZ ORTIZ, MARÍA, Hervas-Martinez, C.
Publicación externa No
Medio Lect. Notes Comput. Sci.
Alcance Proceedings Paper
Naturaleza Científica
Cuartil JCR 4
Cuartil SJR 2
Impacto SJR 0.35400
Web https://www.scopus.com/inward/record.uri?eid=2-s2.0-84902479653&doi=10.1007%2f978-3-319-07617-1_7&partnerID=40&md5=041b4d7a6be5e202bee9004e2287dd5f
Fecha de publicacion 01/01/2014
ISI 000342836300007
Scopus Id 2-s2.0-84902479653
DOI 10.1007/978-3-319-07617-1_7
Abstract The discovery of characteristic time series patterns is of fundamental importance in financial applications. Repetitive structures and common type of segments can provide very useful information of patterns in financial time series. In this paper, we introduce a time series segmentation and characterisation methodology combining a maximal likelihood optimisation procedure and a clustering technique to automatically segment common patterns from financial time series and address the problem of stock market prices trends. To do so, the obtained segments are transformed into a five-dimensional space composed of five typical statistical measures in order to group them according to their statistical properties. The experimental results show that it is possible to exploit the behaviour of the stock market Ibex-35 Spanish index (closing prices) to detect homogeneous segments of the time series.
Palabras clave Clustering; Ibex-35 index; segmentation; stock market; time series
Miembros de la Universidad Loyola

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